VidFare

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare this a safe, non-destructive, closed-world read. The description adds genuine value by disclosing the result shape (overall and per model) and an omission rule for unstated length/resolution combos, which matters because there is no output schema. It stays silent on how the optional audio/input/used/apply_deals filters narrow rows, and on what an empty result looks like.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tightly packed sentences with no filler. The core scope is front-loaded and the omission caveat is a single clause rather than a separate paragraph.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a six-parameter, read-only pricing query with no output schema, the description covers scope, output granularity, and row-omission behavior, which is the important part. It leaves open whether prices are totals or per-second, what currency/plan basis applies, and whether the other filters change which rows are omitted.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all six parameters are already documented in the schema including enums, ranges, and defaults. The description adds no parameter-level meaning beyond the phrase 'for a clip length and resolution', so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource and verb-equivalent: the cheapest *stated* VidFare price for a given clip length and resolution, returned both overall and per model. That is clearly distinguishable from get_model_prices or estimate_cost by intent, though it never names a sibling explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use or when-not-to-use guidance and no mention of the sibling tools (estimate_cost, get_model_prices) it overlaps with. The word 'cheapest' implies comparison shopping, but the agent must infer that this is a ranking tool rather than a cost estimator.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the read-only, non-destructive, closed-world profile. Beyond that, the description discloses the two billing models (credit-plan proration vs API per-second billing) and, importantly, the failure behavior: unstated length/resolution/audio/input yields a result without a price. That edge case is exactly the kind of context an agent cannot infer from the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with purpose, then the two pricing branches, then the edge case. Every sentence carries information, though the credit-plan sentence is dense and reads like a formula transcription rather than agent-directed guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 10-parameter read-only calculation tool with no output schema, the description covers the two computational paths and the no-price case, which is most of what an agent needs to interpret results. It stops short of describing the return shape, particularly the break-even note that window_seconds feeds, which is only alluded to in the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all 10 parameters well, and the baseline is 3. The description adds some semantic weight by naming which inputs (length, resolution, audio, input) can legitimately be missing and what that produces, but it does not clarify the plan-vs-provider interaction that the schema leaves slightly ambiguous.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Opening sentence states a specific quantity (cost of one clip) and the source (the VidFare calculator), which tells an agent this is a compute-one-estimate tool rather than a price listing. It doesn't explicitly distinguish itself from siblings like get_model_prices or cheapest_options, which is the main thing keeping it from a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance and no naming of alternatives. The description explains the math behind the estimate but never says why an agent should call this instead of get_model_prices or cheapest_options, nor what prerequisites (plan vs provider) select which path.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds one genuinely useful behavioral guarantee — that catalog-missing prices are omitted rather than fabricated — which prevents an agent from misreading an absent price as zero. It says nothing about return shape or whether results are sorted, so it sits just at adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences with zero filler, front-loading the action and scope before the filter note and the omission caveat. Every sentence carries distinct information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, and the description does not describe what a returned price record contains (per-provider or per-resolution granularity). For a simple read tool with fully documented parameters it is close to sufficient, but the return surface remains unstated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all three parameters in detail, including examples. The description adds only that provider and resolution are optional filters and that lookup is constrained to a single model, which barely extends the schema. Baseline 3 applies when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('List current VidFare prices') and scopes it to one model, which separates it from list_models and cheapest_options. It does not explicitly name which sibling to use for aggregate or cheapest-price queries, so differentiation is implied rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clarifies that provider and resolution are optional filters, which implies the lookup pattern. It gives no guidance on when to prefer this over cheapest_options or estimate_cost, nor any prerequisite or exclusion.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful context beyond that: deals are sourced from vendor pages and official accounts, and an end date appears only when the source stated one, which warns the agent about missing fields. It stops short of describing result volume, ordering, or pagination.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the core action and provenance, then the filter semantics. The status enumeration duplicates the schema slightly, but nothing is padded or buried.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-optional-parameter read tool with annotations and no output schema, the description covers what is returned, where it comes from, and a key data-quality caveat about end dates. Only result ordering and volume are unaddressed, which is minor here.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the enum already documents live/upcoming/ended/all with the live default. The description restates the same enum values and default rather than adding format or behavioral nuance, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('List VidFare deals') and adds provenance ('copied from vendor pages and official accounts'), which tells an agent what kind of data this returns. It does not explicitly contrast with the sibling tools, but the deal-listing scope is distinct enough from pricing/model tools to be unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: the description explains the status filter and its default, which hints at how to narrow results, but it never says when to reach for this tool versus cheapest_options or get_model_prices, nor any exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds useful context that prices are 'cheapest current' and denominated in dollars per second, but says nothing about result ordering, size, or freshness beyond the word 'current'.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single well-formed sentence with the resource front-loaded and the payoff (cheapest dollars per second) trailing. No filler, no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-parameter, read-only listing tool with no output schema, the description conveys enough about what comes back (model list plus per-second price) to call it correctly. Minor gaps remain around ordering and whether all models or only priced ones are returned.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. No parameter concerns are introduced.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb (list) and resource (AI video models tracked by VidFare) and previews the payload (cheapest current dollars per second per model). It is clear without opening the schema, though it doesn't explicitly contrast itself with siblings like get_model_prices or cheapest_options.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: the zero-parameter shape and 'tracks' wording suggest a catalog/discovery call, but there is no explicit statement of when to choose this over get_model_prices or cheapest_options. An agent must infer the routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.